Systems and methods for processing ECG data

ABSTRACT

A computer-implemented method for processing ECG data may include: receiving ECG data representing a plurality of heartbeats; analyzing the ECG data to determine whether each of the plurality of heartbeats is a normal heartbeat or an abnormal heartbeat; associating each of the abnormal heartbeats with an existing template or a new template; receiving input related to each new template, wherein the input includes either: a) a confirmation that the new template represents an abnormal heartbeat, or b) a reclassification of the new template as representing a normal heartbeat or a different abnormal heartbeat; and in response to the user input, updating a label of each of the heartbeats associated with each confirmed new template and each of the heartbeats associated with each reclassified new template.

TECHNICAL FIELD

Various embodiments of the present disclosure relate to a device andsystems and methods of using the device for health monitoring, and moreparticularly to a device and system and methods of using a device forphysiologic data monitoring.

BACKGROUND

Physiologic data may be used to monitor the health of a patient. Forexample, bioelectric signals (e.g., electrocardiogram or ECG signals)from the patient's heart may be used to monitor cardiac health. ECG is arecording of the electrical activity of the heart. During ECGmonitoring, electrodes attached to a patient's skin are used to detectelectrical activity of the heart over a period of time, and electricalimpulses generated by the heart during each heartbeat are detected andrecorded and/or displayed on a device. Analysis of the data reveals thecardiac health (e.g., rate and regularity of heartbeats, size andposition of the chambers, the presence of any damage to the heart,effects of drugs or devices used to regulate the heart, etc.) of thepatient.

Multiple electrodes (e.g., left arm (LA), right arm (RA), and left leg(LL) electrodes) may be attached to the patient's skin for ECGmeasurement. These electrodes may be combined into a number of pairs(e.g., three pairs LA-RA, LA-LL, and RA-LL), and voltage signals may berecorded across each pair. Each pair is known as a lead. Each lead looksat the heart from a different angle. Different types of ECG measurementscan be referred to by the number of leads that are recorded (e.g.,3-lead, 5-lead, 12-lead ECG, etc.).

Many cardiac problems become noticeable only during physical activity(walking, exercise, etc.). An ambulatory electrocardiogram (ECG)continuously monitors the electrical activity of the heart while apatient does normal activities. Typically, a 12-lead or a 5-lead ECG isused for periodic ECG monitoring (e.g., at a doctor's office, etc.) anda 3-lead ECG is used for continuous ambulatory monitoring. In 3-leadmonitoring, ECG data is collected using three electrodes attached to thepatient. The collected data is recorded in a monitor operatively coupledto the electrodes. The stored data is analyzed by a health careprovider. In some cases, the monitor may transmit ECG data to a healthcare provider for analysis. Several types of monitors (e.g., Holtermonitor, event monitors, mobile cardiovascular telemetry monitors, etc.)are known in the art. Some of these monitors store the data forsubsequent analysis by a health care provider, while others transmit(real-time, periodically, or on demand) the collected ECG data to aremote site where it is analyzed.

SUMMARY

Embodiments of the present disclosure relate to, among other things,devices for physiologic data monitoring. Each of the embodimentsdisclosed herein may include one or more of the features described inconnection with any of the other disclosed embodiments.

A computer-implemented method for processing ECG data may include:receiving, over an electronic network, ECG data, wherein the ECG datarepresents a plurality of heartbeats; analyzing the ECG data, by atleast one processor, to determine whether each of the plurality ofheartbeats is a normal heartbeat or an abnormal heartbeat; associating,by the at least one processor, each of the abnormal heartbeats witheither only one of a plurality of existing templates or a new template;receiving, from a user, input related to each new template, wherein theinput includes either: a) a confirmation that the new templaterepresents an abnormal heartbeat, or b) a reclassification of the newtemplate as representing a normal heartbeat or a different abnormalheartbeat; and in response to the user input, updating, by the at leastone processor, a label of each of the heartbeats associated with eachconfirmed new template and each of the heartbeats associated with eachreclassified new template.

A system for processing ECG data may include a data storage device thatstores instructions for processing ECG data; and a processor configuredto execute the instructions to perform a method including: receiving,over an electronic network, ECG data, wherein the ECG data represents aplurality of heartbeats; analyzing the ECG data to determine whethereach of the plurality of heartbeats is a normal heartbeat or an abnormalheartbeat; associating each of the abnormal heartbeats with either onlyone of a plurality of existing templates or a new template; receiving,from a user, input related to each new template, wherein the inputincludes either: a) a confirmation that the new template represents anabnormal heartbeat, or b) a reclassification of the new template asrepresenting a normal heartbeat or a different abnormal heartbeat; andin response to the user input, updating the labels of each of theheartbeats associated with each confirmed new template and each of theheartbeats associated with each reclassified new template.

A non-transitory computer-readable medium may store instructions that,when executed by a computer, cause the computer to perform a method forprocessing ECG data, the method including: receiving, over an electronicnetwork, ECG data, wherein the ECG data represents a plurality ofheartbeats; analyzing the ECG data, by at least one processor, todetermine whether each of the plurality of heartbeats is a normalheartbeat or an abnormal heartbeat; associating, by the at least oneprocessor, each of the abnormal heartbeats with either only one of aplurality of existing templates or a new template; receiving, from auser, input related to each new template, wherein the input includeseither: a) a confirmation that the new template represents an abnormalheartbeat, or b) a reclassification of the new template as representinga normal heartbeat or a different abnormal heartbeat; and in response tothe user input, updating, by the at least one processor, a label of eachof the heartbeats associated with each confirmed new template and eachof the heartbeats associated with each reclassified new templates.

A method, system, or non-transitory computer-readable medium forprocessing ECG data may additionally or alternatively include one ormore of the following steps or features: the method does not includerepeating the analyzing step; the method may further comprise totaling,by the at least one processor, the number of heartbeats associated withthe confirmed new templates and the number of heartbeats associated withthe new templates reclassified as a different abnormal heartbeat; theassociating step may include comparing ECG data representing a heartbeatto at least one of the plurality of existing templates; the step ofassociating may include creating the new template for abnormalheartbeats having characteristics that differ by more than a predefinedthreshold from each of the existing templates; the step of associatingan abnormal heartbeat with one of the plurality of existing templatesmay include associating the abnormal heartbeat with an existing templateif the abnormal heartbeat has characteristics that differ by less than apredefined threshold from the existing template; the abnormal heartbeatsmay include premature ventricular contractions; the electronic networkmay include a wireless connection over a cellular network; and thereceiving step may include receiving the ECG data from a monitor, andthe monitor may be a portable device configured to be carried on apatient's body.

It may be understood that both the foregoing general description and thefollowing detailed description are exemplary and explanatory only andare not restrictive of the invention, as claimed.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are incorporated in and constitute apart of this specification, illustrate exemplary embodiments of thepresent disclosure and together with the description, serve to explainthe principles of the disclosure.

FIG. 1 illustrates an exemplary system for measuring ECG of a patient.

FIG. 2 illustrates an exemplary device used in the ECG measurementsystem of FIG. 1.

FIGS. 3 and 4 illustrate steps in an exemplary process for detecting andclassifying arrhythmias.

DETAILED DESCRIPTION

Overview of a System for Monitoring Physiologic Data

Embodiments of the present disclosure may include methods and systemsfor monitoring physiologic data of a patient. Various aspects of thepresent disclosure may be used in combination with, or include, one ormore features disclosed in U.S. Pat. No. 8,478,418 (issued Jul. 2, 2013)and U.S. Pat. No. 8,620,418 (issued Dec. 31, 2013), each of which isincorporated by reference herein in its entirety. While an exemplaryembodiment of measuring ECG data is described below, it should be notedthat the current disclosure may be applied to the measurement of anyphysiologic data. For example, the disclosed systems and methods may beused to measure signals indicative of heart rate, activity level (e.g.,physical mobility or movement), respiration rate, blood pressure (e.g.,systolic and/or diastolic), blood oxygen saturation (SpO2), bloodglucose or insulin level, pulse oximetry, impedance, body temperature,etc. Thus, the systems, devices, and methods described herein mayacquire and process other types of physiologic data instead of or inaddition to ECG data. It is also contemplated that, in some embodiments,the measured physiologic data may be used to determine a cardiac safetyindicator such as QT prolongation, ST elevation, etc.

FIG. 1 is a schematic illustration of an exemplary system 100 formeasuring ECG of a patient 10. A plurality of electrodes 14, 16, 18 maybe attached to the patient 10 to detect ECG signals. Although athree-electrode configuration is illustrated, electrodes may be placedto measure any number of leads (e.g., a 10 electrode, 12-leadconfiguration). In one example, the electrodes 14, 16, 18 acquire twoleads (channels) of ECG data. The electrodes 14, 16, 18 detect (and insome cases amplify) tiny electrical changes on the skin that are causedwhen heart muscles depolarize during each heartbeat. At rest, each heartmuscle cell has a negative charge (called the membrane potential) acrossits cell membrane. Decreasing this negative charge toward zero, via theinflux of the positive cations (Na+ and Ca++) is called depolarization.Depolarization activates mechanisms in the cell that cause it tocontract. During each heartbeat, a healthy heart will have an orderlyprogression of a wave of depolarization that is triggered by the cellsin the sinoatrial node, spreads out through the atrium, passes throughthe atrioventricular node and then spreads all over the ventricles. Thedepolarization wave (or ECG data) is indicative of the overall rhythm ofthe heart and is detected as variations in voltage between the electrodepairs (e.g., between electrodes 14-16, 14-18, and 16-18).

System 100 may include a monitor 20 operatively coupled to theelectrodes 14, 16, 18. Monitor 20 may be adapted to receive and storethe ECG data from the electrodes 14, 16, 18 using standard connectionsknown in the art (e.g., lead wires, an analog to digital converter,etc.). In one example, the lead wires connected to each electrode inFIG. 1 may include a resistor. If a patient is undergoingdefibrillation, the resistor may prevent the monitor from divertingenergy applied to the patient by the defibrillation device. The presenceof resistors in the lead wires does not inhibit impedance tomography. Inone example, the resistor in each lead wire may be 1000 ohms.

In addition to the connection to electrodes 14, 16, 18, the monitor 20may be configured to communicate with one or more additional oralternative sensors via wired or wireless connections. Any combinationof well-known physiological sensors may be coupled to the monitor 20,such as SpO2 sensors, blood pressure sensors, heart electrodes (e.g.,electrodes 14, 16, 18), respiration sensors, movement and activitysensors, glucose monitors, and the like. Respiration data may be derivedfrom ECG baseline data, as is known to those of skill in the art. In oneexample, the monitor 20 can connect to a sensor in a scale to receiveinformation related to the patient's weight. Movement or activity may besensed with appropriate accelerometers or gyroscopes, which may includemicro electro-mechanical system (MEMS) devices. The one or moreadditional or alternative sensors may be connected to the monitor 20 viawires or optical cables or via a wireless link (e.g., Bluetooth, Wi-Fi,ZigBee, Z-wave, radio, etc.).

In one example, at least one type of sensor transmits data to themonitor 20 via a wired connection, and at least one type of sensortransmits data to the monitor 20 via a wireless connection. The patient10 may press a button on the monitor 20 to wirelessly pair it with oneor more of the sensors described above. In another example, a user maycommunicate with a monitor 20 via a web/mobile interface component towirelessly pair the monitor 20 with selected sensors.

In some embodiments, monitor 20 may transfer at least a portion of themeasured ECG data (or other physiologic data) to a remote analysisstation 60 for analysis. Although analysis station 60 is illustrated asa computer (e.g., processor and memory), in general, analysis station 60may include any collection of computational devices (e.g., one or moreservers, databases, and computers networked together) and personnel. Theterm “processor” as used herein may include a central processing unit ora microprocessor. The ECG data from monitor 20 may be transferred toremote analysis station 60 over a wired connection, using a portablestorage medium (transferable memory device, etc.), or wirelessly over atelecommunications network 50 (e.g., a cellular network, the Internet, acomputer network, etc.). For example, monitor 20 may include a cellularmodem, and the ECG data may be sent to the analysis station 60 via acellular network. As used herein, the term “electronic network” mayinclude any combination of wired and wireless communication technologiesused to transmit information.

Analysis station 60 may analyze the ECG data to check the cardiac healthof patient 10. Any analysis methodology known in the art may be used toanalyze the received data (e.g., a methodology described by Philip deChazal, et al., in “Automatic Classification of Heartbeats Using ECGMorphology and Heartbeat Interval Features,” IEEE Transactions onBiomedical Engineering, Vol. 51, No. 7, July, 2004). In someembodiments, monitor 20 may at least partially analyze the collected ECGdata before it is transferred to analysis station 60.

In some embodiments, monitor 20 may store the collected ECG data, andcontinuously transmit (directly or through an intermediate device) asubset of the data (e.g., data at a lower resolution, etc.) to theanalysis station 60. In one example, the subset of the data istransmitted at 100 samples per second, although it may be transmitted at200 samples per second or at any other frequency. The analysis station60 may analyze the received data to determine if it indicates an anomaly(e.g., an arrhythmia, an unexpected trend in the data, etc.). If ananomaly is indicated, analysis station 60 may request (i.e. transmitinstructions) the monitor 20 for more data (e.g., data from the sametime frame at a higher resolution, etc.). For example, if the initialdata was transmitted at 100 samples per second, the second set of moredetailed data may be transmitted at 200 samples per second. Upon receiptof this request, the monitor 20 may retrieve the requested data frommemory and transmit it to the analysis station 60. The analysis station60 may then analyze the data (e.g., using a more rigorous analysismethodology) to confirm or refute the anomaly detected during theprevious analysis. This analysis methodology is described in more detailin U.S. Pat. No. 8,478,418, which is incorporated by reference herein.

Monitor

FIG. 2 illustrates an exemplary embodiment of monitor 20. Monitor 20 mayinclude integrated circuits (microprocessor, memory, communicationdevices, etc.), visual displays (LED, LCD, etc.), and/or buttons thatcan be activated by the patient 10. The integrated circuits of monitor20 may enable processing of collected ECG data, and communicationbetween monitor 20 and the analysis station 60. The buttons may enablethe patient 10 to trigger an activity (data collection, communicationwith analysis station 60, record or mark an event, etc.), and thedisplay may enable the monitor 20 and analysis station 60 to communicatewith patient 10 (e.g., using text messages). In one embodiment, themonitor 20 may include dimensions of approximately 108 mm×67 mm×17 mm,although the monitor 20 may be any size that allows it to be portablewith the patient.

Monitor 20 may be a portable device, sized and adapted to be kept in thepossession (strapped, attached, placed in the pocket, etc.) of patient10. Such a portable monitor 20 may enable the patient 10 to go about thepatient's daily activities while the monitor 20 records (and/ortransfers, analyzes, etc.) ECG data. In the exemplary embodimentillustrated in FIG. 1, monitor 20 is shown as a device attached by aconnector (e.g., clipped) to the patient's belt. However, this is onlyexemplary, and other configurations are possible (e.g., the connectorcould allow the device to be worn around the patient's neck). Inembodiments where electrodes 14, 16, 18 are connected by a wire to themonitor, monitor 20 may include a connector to receive the connectingwire. In embodiments where electrodes 14, 16, 18 are coupled wirelessly,monitor 20 may include a transceiver to communicate with a transceiverof electrodes 14, 16, 18.

In one embodiment, the monitor 20 may include an event button 22, a wakebutton 24, and a volume button 26. A physician may press the eventbutton 22 to activate the monitor 20 for patient use. Furthermore, thepatient 10 may press the event button 22 if a symptom, such as thefeeling caused by an arrhythmia, occurs. However, the monitor 20 maycontinuously record ECG data whether or not the patient presses theevent button 22. Information from the event button 22 may thereforeserve to help confirm suspected arrhythmias or other irregular heartactivity detected from the ECG data. The wake button 24 may be pressedby the patient 10 to display the current level of reception (e.g., via acellular network), the battery level, and/or whether the electrodes 14,16, 18 are adequately coupled to the patient 10. Upon pressing the wakebutton 24, a light 34 may be green if the electrodes are all adequatelycoupled to the patient or red if one or more of the electrodes is notadequately coupled to the patient. The volume button 26 may allow thepatient 10 to adjust or mute the volume of alerts from the monitor 20.

The monitor 20 may include a display 28. The display 28 may include aplurality of LED lights and one or more icons underneath the outercasing of the monitor. The LED lights may form an LED matrix 45 (e.g.,24×7, 20×7, or any other suitable arrangement of lights). In oneembodiment, when the lights are off, the display is either imperceptibleor faintly visible. When one or more LED lights or icons are lit,however, the individual lights or icons may be visible through theportion of the outer casing of the monitor that overlays the display 28.That portion of monitor 20 (a window over display 28) may be made of atransparent or semi-transparent material, for example, translucentpolycarbonate.

A variety of display patterns may appear on the display 28 at varioustimes to provide information to the patient 10. In FIG. 2, for example,the display pattern 28 a may include a wireless icon 30 and a batteryicon 32, which each correspond to one or more columns (e.g., three) ofLED lights. Display pattern 28 a may appear when the user (e.g., aphysician, nurse, technician, patient, or any other person) presses thewake button 24. The columns of LED lights may indicate the level ofwireless service and the battery level, respectively. Display pattern 28b may include an icon shaped like a heart, which may be displayed whenthe event button 22 is pressed. Display pattern 28 c may include aspeaker and rows of LED lights, and may be displayed when the userchanges the volume. The number of rows of LED lights may increase whenthe volume is raised and decrease when the volume is lowered. “Mute” maybe spelled in LED lights next to a speaker icon when the sound is muted.When one or more electrodes is not connected to the patient 10, thewords “lead off” may scroll across the LED display, as shown in displaypattern 28 d. Alternatively, the words “lead” and “off” may alternate onthe display 28. Display pattern 28 e may appear when the battery is low.The number of rows of LED lights that appear may correspond to the levelof battery remaining. Furthermore, the battery icon may appear red toindicate low battery status. In a final example, display pattern 28 fmay appear if there is an error that requires user attention. The LEDlights may be lit in any suitable pattern or may form any words tocommunicate to the patient 10.

In other examples, display 28 may be separate from the monitor 20. Theseparate display 28 could be a stand-alone display or could be a user'scell phone or other communication device. The monitor 20 may transmitinformation to the stand-alone display, cell phone, or othercommunication device via any type of wireless network.

The monitor 20 may include a rechargeable battery. In one example, thebattery may operate for between 24 and 72 hours on a single charge. Thebattery may be removable from the monitor 20 and docked to an externalcharger.

The hardware of monitor 20 may include various components connected bygeneral purpose input/outputs or by specialized connectors. The hardwaremay include any suitable microprocessor and other circuitry known to oneof ordinary skill in the art for performing the various functions of thesystem described herein, such as analog-to-digital converters,device/component drivers, transceivers, and memory. The system softwaremay receive ECG data for evaluation by an arrhythmia analysis algorithm,and any detected arrhythmias may be identified and presented forphysician review. The system software may detect, for example, prematureventricular contractions (PVCs) from the ECG data, as will be describedfurther below.

Method for Processing of ECG Data

FIGS. 3 and 4 illustrate an automated method for processing ECG data todetect arrhythmias, or abnormal heartbeats. Although an exemplaryembodiment of detecting premature ventricular contractions (PVCs) isdescribed, the method can be used to detect any type of irregularheartbeat. The illustrated method may require less computationalresources and may process ECG datasets with greater speed than existingmethods of processing ECG data to detect PVCs. PVC detection may play arole in diagnosing a variety of heart conditions, including: heartattack, high blood pressure, cardiomyopathy (including congestive heartfailure), disease of heart valves (such as mitral valve prolapse),hypokalemia (low blood levels of potassium), hypomagnesemia (low bloodlevels of magnesium), and hypoxia (low amounts of oxygen in the blood).In addition, several PVCs in a row with a high heart rate could indicatea serious arrhythmia, such as ventricular tachycardia.

Automatic classification of PVCs presents a challenge. For example, apatient may have over 100,000 heartbeats every day. Even if an automaticprocess/algorithm is 99% accurate, about 1000 beats per day may bemisclassified. Time-consuming human validation may then be required tocorrect misclassifications. Some existing classification processes mayrequire an entire ECG data set to be processed twice—a first processingto detect suspected PVCs and a second processing after receiving userinput related to the suspected PVCs.

A method for detecting and classifying PVCs may include receiving ECGinput/data. In one example, the original ECG data may be sampled at 1024samples per second, although any other sampling rate may be used (e.g.,2048, 512, 256, etc.). The ECG input may undergo appropriate filteringand processing steps to, for example, eliminate noise; reduce the datato a lower number of samples per second, such as 200 or 100; and/ordetect the amplitudes and/or thresholds of beats. This information maybe used to detect PVCs. For example, PVC beats may have a higheramplitude than normal beats, and beats may be classified as PVC if theyhave a threshold over a fixed reference threshold.

Detected heartbeats may be labeled or classified as either: a) normal,or b) PVC. The PVC beats may be provided with a PVC template IDcorresponding to their morphology (e.g., the duration and amplitude ofthe various waves/intervals/complexes). A PVC “template” is, forexample, a representation of a suspected PVC beat that is derived from(e.g., is an average of) the characteristics of a plurality of suspectedPVC beats having a similar morphology. Each template may therefore beassociated with a plurality of beats having a certain morphology. Eachtemplate may have a unique template ID. Each patient 10 may have aplurality of different PVC templates, with each template correspondingto beats having a certain morphology.

FIG. 3 illustrates an exemplary method for determining whether to createa new PVC template. The method begins at step 600 with a suspected PVCbeat that was detected, as described above. In step 610, the morphologyof the suspected PVC may be compared to stored, previously-existing PVCtemplates (if there are any) to determine whether a template for thesuspected PVC is known. The previously-existing PVC templates may betemplates that were developed from earlier-processed heartbeats from thesame patient. Additionally or alternatively, the previously-existing PVCtemplates may be based on known morphologies of PVCs, based on, forexample, a population of patients. If the difference between thesuspected PVC and the existing templates is above a certain threshold, anew PVC template may be created for the suspected PVC (step 620). In oneexample, the threshold may be 5% in absolute differences between one ormore of the characteristics that define the morphology of a heartbeat(e.g., the duration and amplitude of the variouswaves/intervals/complexes). However, if the morphology of the suspectedPVC is similar to an existing template (e.g., below a certainthreshold), the PVC beat may be added to the existing template (step630). In step 640, the templates are sent to a user for review.

FIG. 4 illustrates a method for user review of PVC templates. In step700, the user reviews a PVC template. The user then determines whetherthe template is a PVC (step 710) and provides input to thehardware/software that analyzes the ECG data to determine arrhythmias.In one example, the user may complete step 710 by reviewing theinformation from the template, such as the duration and amplitude ofvarious waves/intervals/complexes (e.g., the QRS complex), anddetermining whether the heartbeat is irregular when compared to thepatient's normal heartbeat. Additionally or alternatively, the usermight compare the information from the template to other knowninformation about irregular heartbeats. If the user determines that thetemplate does not represent a PVC, the template ID may be deleted fromthe PVC count (step 720), along with all beats associated with thattemplate ID. Furthermore, the labels associated with each heartbeatcorresponding to the deleted PVC template may be updated to indicatethat the heartbeats are not PVCs. However, if the user determines thatthe template does represent a PVC, the template ID may be added to thePVC count (step 730). In other words, if the template ID is confirmed asa PVC by the user, all beats associated with the template ID may beconfirmed and added to the PVC count, and the labels associated witheach confirmed heartbeat may be updated to indicate that the heartbeatsare PVCs. The beats associated with all of the valid PVC template IDsmay then be added to determine the total PVC count.

Accordingly, the ECG data may be processed once to detect potentialPVCs. The remaining steps of the PVC processing method may then rely onthe beat labels (e.g., normal or PVC with a template ID), which may beabout 200 times smaller in data size compared to the original ECG data.Because the process of FIG. 4 relies on beat labels and eliminates theneed for all of the ECG data to be reprocessed to classify and totalPVCs based on the user's input, the process can be carried out moreefficiently than previously existing classification methods.

At the end of a pre-defined interval (e.g., a day), the total number ofPVC beats may be calculated. In one example, if the total number is morethan a predefined threshold (e.g., 100), the PVC statistics may bedisplayed by one or more of the monitor 20 or by a device used by theclinician for review.

While principles of the present disclosure are described herein withreference to illustrative embodiments for particular applications, itshould be understood that the disclosure is not limited thereto. Thosehaving ordinary skill in the art and access to the teachings providedherein will recognize additional modifications, applications,embodiments, and substitution of equivalents all fall within the scopeof the embodiments described herein. Accordingly, the invention is notto be considered as limited by the foregoing description.

We claim:
 1. A computer-implemented method for processing ECG data,comprising: receiving, over an electronic network, ECG data, wherein theECG data represents a plurality of heartbeats; analyzing the ECG data,by at least one processor, to determine whether each of the plurality ofheartbeats is a normal heartbeat or an abnormal heartbeat; associating,by the at least one processor, each of the abnormal heartbeats with alabel of: at least one template of a plurality of existing templates, ora new template; after the associating of all of the abnormal heartbeats,receiving from a user, user input related to each new template, whereinthe user input includes either: a confirmation that the new templaterepresents an abnormal heartbeat, or a reclassification of the newtemplate as representing a normal heartbeat or a different abnormalheartbeat; after receiving the user input, updating, by the at least oneprocessor, the label of each new template to correspond with the userinput; and determining, by the at least one processor, a number ofabnormal heartbeats as a sum total of the heartbeats associated with (i)each template of the plurality of existing templates, (ii) eachconfirmed new template representing an abnormal heartbeat, and (iii)each new template reclassified as a different abnormal heartbeat, usingthe labels associated with the existing, confirmed new, and newreclassified templates.
 2. The method of claim 1, wherein the methoddoes not include repeating the analyzing step.
 3. The method of claim 1,wherein the associating step includes comparing ECG data representing aheartbeat to at least one of the plurality of existing templates.
 4. Themethod of claim 1, wherein the step of associating includes creating thenew template for abnormal heartbeats having characteristics that differby more than a predefined threshold from each of the existing templates.5. The method of claim 1, wherein the step of associating an abnormalheartbeat with one of the plurality of existing templates includesassociating the abnormal heartbeat with an existing template if theabnormal heartbeat has characteristics that differ by less than apredefined threshold from the existing template.
 6. The method of claim1, wherein the abnormal heartbeats include premature ventricularcontractions.
 7. The method of claim 1, wherein the electronic networkincludes a wireless connection over a cellular network.
 8. The method ofclaim 1, wherein the receiving step includes receiving the ECG data froma monitor, and wherein the monitor is a portable device configured to becarried on a patient's body.
 9. A system for processing ECG data,comprising: a data storage device that stores instructions forprocessing ECG data; and a processor configured to execute theinstructions to perform a method including: receiving, over anelectronic network, ECG data, wherein the ECG data represents aplurality of heartbeats; analyzing the ECG data to determine whethereach of the plurality of heartbeats is a normal heartbeat or an abnormalheartbeat; associating each of the abnormal heartbeats with a label of:at least one template of a plurality of existing templates, or a newtemplate; after the associating of all of the abnormal heartbeats,receiving from a user, user input related to each new template, whereinthe user input includes either: a confirmation that the new templaterepresents an abnormal heartbeat, or a reclassification of the newtemplate as representing a normal heartbeat or a different abnormalheartbeat; after receiving the user input, updating the label of eachnew template to correspond with the user input; and determining a numberof abnormal heartbeats as a sum total of the heartbeats associated witha (i) each template of the plurality of existing templates, (ii) eachconfirmed new template representing an abnormal heartbeat, and (iii)each new template reclassified as a different abnormal heartbeat, usingthe labels associated with the existing, confirmed new, and newreclassified templates.
 10. The system of claim 9, wherein the methodperformed by the processor does not include repeating the analyzingstep.
 11. The system of claim 9, wherein the step of associatingincludes comparing ECG data representing a heartbeat to at least one ofthe plurality of existing templates.
 12. The system of claim 9, whereinthe step of associating includes creating the new template for abnormalheartbeats having characteristics that differ by more than a predefinedthreshold from each of the existing templates.
 13. The system of claim9, wherein the step of associating an abnormal heartbeat with one of theplurality of existing templates includes associating the abnormalheartbeat with an existing template if the abnormal heartbeat hascharacteristics that differ by less than a predefined threshold from theexisting template.
 14. The system of claim 9, wherein the abnormalheartbeats include premature ventricular contractions.
 15. Anon-transitory computer-readable medium storing instructions that, whenexecuted by a computer, cause the computer to perform a method forprocessing ECG data, the method including: receiving, over an electronicnetwork, ECG data, wherein the ECG data represents a plurality ofheartbeats; analyzing the ECG data, by at least one processor, todetermine whether each of the plurality of heartbeats is a normalheartbeat or an abnormal heartbeat; associating, by the at least oneprocessor, each of the abnormal heartbeats with a label of: at least onetemplate of a plurality of existing templates, or a new template; afterthe associating of all of the abnormal heartbeats, receiving from auser, user input related to each new template, wherein the user inputincludes either: a confirmation that the new template represents anabnormal heartbeat, or a reclassification of the new template asrepresenting a normal heartbeat or a different abnormal heartbeat; afterreceiving the user input, updating, by the at least one processor, thelabel of each new template to correspond with the user input; anddetermining, by the at least one processor, a number of abnormalheartbeats as a sum total of the heartbeats associated with (i) eachtemplate of the plurality of existing templates, (ii) each confirmed newtemplate representing an abnormal heartbeat, and (iii) each new templatereclassified as a different abnormal heartbeat, using the labelsassociated with the existing, confirmed new, and new reclassifiedtemplates.
 16. The method of claim 15, wherein the method does notinclude repeating the analyzing step.
 17. The method of claim 15,wherein the associating step includes comparing ECG data representing aheartbeat to at least one of the plurality of existing templates. 18.The method of claim 15, wherein the step of associating includescreating the new template for abnormal heartbeats having characteristicsthat differ by more than a predefined threshold from each of theexisting templates.
 19. The method of claim 15, wherein the step ofassociating an abnormal heartbeat with one of the plurality of existingtemplates includes associating the abnormal heartbeat with an existingtemplate if the abnormal heartbeat has characteristics that differ byless than a predefined threshold from the existing template.
 20. Themethod of claim 15, wherein the abnormal heartbeats include prematureventricular contractions.